Hi, what's up Toby?
We have made it to the Process Debt Podcast episode number eight.
Today, we will be talking about virtuous cycles.
Now, virtual cycles, those can be great.
Virtual or virtuous?
Which cycle?
Virtuous. Let's do virtuous.
Well, virtual cycles is on a future episode.
How's that?
Virtual cycles.
The power of virtual process.
It's like virtual currency.
It is.
Sounds good.
That's how you retire young like us.
It's a technology finding a problem.
No, virtuous cycles.
And one of the patterns that I've recently noticed,
and actually as I noticed it, I was like, oh man, that happens a lot.
Which is when I believe that knowledge work is a lot about the transfer
of knowledge, right?
Specifically in business processes, it's the transfer of that knowledge.
Whereas if you're a developer, it's basically transferring.
A lot of times it's transferring of data.
It's slightly different.
But there's this unvirtuous cycle, which is we deliver a deliverable.
A lot of times those deliverables can be a PowerPoint, a Word doc, a Confluence page.
Could be any roadmap, whatever.
We deliver that.
And oftentimes those send poor signals.
Meaning there's something different in this presentation than my peer gave
in their presentation.
So now we're in mixed messaging.
Yeah.
So there's this mixed signal between the two groups because there's no
consistency in what the deliverable is.
And so I work in a product org.
And so we have X amount of product people.
And if I deliver something and then my peer delivers something and it's
different, whoever went second or whoever has the ugliest looking presentation
has basically sent a signal, a poor signal, a signal of poor quality.
And that leads to kind of a, if I'm the receiver of that knowledge, I don't
trust either that person or sometimes the entire org, right?
Or the entire delivery process of whatever.
And so what the unvirtuous cycle happens is what that leads to is more control.
In the absolute purity.
You have to lean into it and really get more actively engaged.
Okay.
Correct.
But the control is misaligned.
Yeah.
So the control is actually aligned to fixing the signal.
As opposed to the outcome that we were trying to move towards.
Correct.
Yeah.
Love it.
I love it.
Which is this.
And so then what happens is you have this change, right?
And that's fine.
Change happens, right?
Yeah.
One of the gains that we have is gradual change, right?
Like being disciplined in how you do these changes, especially if there's
more than one person, because if it's one person giving an analysis, you have
no cohort to compare it to.
But if you have a cohort to compare your deliverables to and there's one of these
things is not like the other or everything is inconsistent, it's just rough.
And so more control to improve the signal, which leads to rework, right?
Or change in what's being delivered, which leads to confusion, which leads to poor
signals, which is this just un-virtuous cycle that's just around and around and
around.
Yeah.
Chris, that reminds me of, and I'm sure we've all seen the memes where it's like,
I will perform this task for $100 an hour.
If you ask me what I'm doing, it's 150.
Yeah.
If you want to weigh in on my initial design before I deliver it, it's 200.
Yep.
You know, it just, and so I think that little meme that we've all seen where the
more involved the receiver of the outcome is, the higher the cost, I think that's a
very true thing.
And that's the human in it, right?
What you're describing is like, if in our race to all have access to information,
you know, all of a sudden we've eroded the base of our expert.
Yeah.
Because to your point about if I have two presentations and they don't match,
my first question is, well, who's the most expert resource?
And the reality is, is it doesn't matter.
It's whichever one's prettier.
It is like that.
That sounds ridiculous.
But if one, OK, like, tell me this, right?
You have an expert, they have a misspelling.
Yeah. Right.
You have someone who's new, fresh, excited and has a pretty PowerPoint.
That's right.
You're going to because you're like that there's a signal mismatch, right?
Where it's like, oh, I'm not like I'm lose like there's a trust drop or something.
I don't know what it is, to be honest.
But it's like when that happens, especially as the closer gets to the CEO,
because it needs to be polished and polished and polished, the closer gets to the CEO.
Like if the CEO sees a misspelling from an expert that's been at the company for 35 years.
And they see something from a consultant, let's say a consultant, let's go with McKinsey for fun,
or whoever, Boston, whoever, pick your consultant.
But if they compare those, right, and there's a misspelling by the internal person
versus the professional polished McKinsey stuff, they will almost always go with that professional polished look.
It's almost human nature.
You know, what's funny to me, Chris, is that we've talked a lot about both of us came into the work world at the at the burgeoning of the Internet, right?
Yeah. And I think just the little Delta in our age, you guys probably had email as a foregone conclusion as you entered.
Oh, my gosh. The funniest thing. So freshman year of college email is out. Right. Yeah.
We are. It was literally like the most awesome thing. We would go down to the computer lab.
Get this. We didn't have computers in our pocket. We had to. We even have computers in our room.
I think we had a typewriter. I'm pretty sure. Anyway, this is totally dating myself.
So go down. You would go down and people would like be staying up till four in the morning because you could send an email back and forth.
It was hilarious. Anyway, that's it. I love that. What's funny is that I think we referred to it in the early days as democratizing information.
Oh, yeah. Yeah. And if you make it available, then people will see it on the on the face of its merits.
And I think instead, what we've discovered is the million ways that we can spin things to our own cause.
And so in today's world, it's hard to discern because most of it, very few of us are experts in every topic we touch.
So, yeah, yeah, yeah. It does take time to to really appreciate what makes an expert.
So if you're new to the topic, everybody around you seems to know more.
And that's that Dunning-Prigger curve. They all know just enough to be dangerous, but they don't all admit it.
Yeah. Yeah. You know, it's interesting.
Like, if you go to like so I was thinking through the on virtuous cycle.
If you look at the virtuous cycle, by contrast, right.
What's by contrast, it starts with the grounding, right.
Which is when I receive, you know, something that's delivered or, you know, the knowledge work piece of work, when that's received, there needs it needs to be grounding, meaning it's consistent.
Right. So it also needs it also needs to, by definition, define like how big this is.
Yeah. Right. And the and the area. Right. So like you kind of there needs to be some multiple things.
There's probably more than that. But like, you know, I think of that of like that that.
I think if let's say it's delivery is a PowerPoint, I think it should be.
Ten pages, completely standard stock, right.
With two pages of autonomy, you do whatever the heck you want on those two pages.
Right. Because we as humans, if we don't have autonomy, we're going to lose our mind.
But it but again, it starts with that grounding, which leads to a familiarity, which should be boring.
Yeah. That context should be familiar for the majority. Right. Correct. Correct.
And there should be that boringness, right. Should also expose the exceptions.
Because the exceptions are what the receiver should care about.
And then those exceptions should should lead you to the identifiable root cause,
which should lead to a solution, which leads to trust, right, which is kind of that that virtual cycle.
So those are just that's my musings of the day.
Chris, it makes me it makes me wonder generationally, you know, and then and then depending on the kind of expertise that you've developed,
what is true can be a lot harder to discover.
And so it does make me wonder if a significant number of leaders have simply have simply failed to keep pace with how they identify what's true.
No, you know, if if the two power points feel like they carry equal merit,
I don't know if that's the byproduct of not understanding the nature of data manipulation or if it's that everybody is maybe so transient now that there's few experts.
Yeah, what's what's interesting is I've thought about the QPR process.
Yeah. Of like if you were if you were, you know, if I was to do some consulting on that QPR process,
I would literally create a Microsoft form, a job form.
I don't care what form it is. Yeah. Where it's literally prescriptive.
Fill out the stupid thing. Yeah. It's a status report.
Correct. Fill out fill out the thing. Yeah. Right.
Then give it to your design team to make the power points and then polish them.
Yeah. Right. Like that would be a very, very efficient and like elegant workflow.
And then what you could do, right, since you've got this all in a form, you basically say we're going to change one thing per quarter.
So you add, subtract. The other thing is you've got it in a form.
So if you want to say what the people said before.
You could just go back and check it right like like you could say, hey, look, you know, Joe, what?
Yeah. Wait a second.
Last time you said it was going to be this. What happened?
What I what I love about that and suggesting listeners take one more lap here,
because what I like about that idea is that when we create a history and when we maintain some consistency,
we can see the anomalies. Yeah.
And we can kind of backtrack to see what the prior information was. Yeah.
And I think that's how we develop a collective IQ.
You know, we have to be able to reference and recontextualize new decision.
Every time we try to radically transform, you know, and and unlock synergies and all the buzzword being that I think doesn't really mean anything anymore,
because nobody knows what it means or how it's used.
All we've done is it's it's like this word vomit. So, yeah, of course, we need more meetings and we need more power points.
Can you craft two more memos and give me a tick tock dance on that?
Well, and you and I worked on that cash flow calculator. Yeah.
That was just it just basically like, look, here's your scenarios, right.
It locks down. Right. You could go and basically say, look, this is what I predicted.
And then how well do you predict? Right.
Because I guarantee you there's three options when you do a prediction prediction.
You're either you're either lucky or wrong. Right.
Lucky being right and wrong being you, you are overly optimistic.
Yeah. Or you're you're under you're pessimistic. Yeah. Right.
Like there's there's no difference.
And I think sometimes like that, there's there's no mechanism to say, what did you predict and how accurate were you?
So anyway, we are way over.
We have we have we have gone to the 13 minute mark.
We are going to call it.
Well, that's what happened. You know, Joe. So I know. I know.
Should have been good stuff. Thank you, sir. Good stuff, man.
What a great what a great. Yeah, what a great talk.
We'll catch you next time, man. All right.
Snake. All right. Yeah. All right. Bye.